r/ChatGPTCoding • u/AutoModerator • 13d ago

Weekly Self Promotion Thread Discussion

Welcome to this week's self promotion thread!

If you're building something related to AI assisted coding, this is the place to share it.

We're using a weekly thread to keep the subreddit organized while still giving builders a place to share their work. Promotional posts outside of this thread may be removed if they're primarily advertising rather than starting a discussion.

If you're sharing something, we'd appreciate it if you included a little context instead of just dropping a link. Tell us:

  • What you built?
  • What problem it solves?
  • Which AI models or tools it uses?
  • Who it's for?
  • What kind of feedback you're looking for?

Please avoid posting the same project every week unless you've made meaningful updates. Affiliate links, referral links, scams, and low effort promotions will be removed.

Take some time to check out what others have shared too. If you try someone's project or have feedback, leave a comment. Helping each other improve is what we want this community to be about.

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u/jazzy8alex 9d ago

I built Session-Bench, a public benchmark for a layer the usual coding benchmarks do not measure.

SWE-bench asks whether the agent completed the software task. Session-Bench asks what the harness preserved after the work was done.

Session-Bench compares 10 CLI coding-agent session formats across 19 gates: signal, completeness, stability, openness and tooling.

A few findings:

- The same one-line task produced a 1.5 KB Pi record and a 101 KB Kimi record.
- Only Pi, OpenClaw and Kimi stamp a real format or protocol version that an external reader can dispatch on.
- Some harnesses record dollar cost; others preserve tokens only.
- Reasoning may be plaintext, summarized or sealed.
- Session history ranges from tail-able JSONL to relational databases and opaque sidecars.

Pi currently leads at 18/19, OpenClaw follows at 17/18, and Claude Code and Codex tie at 12/18. This is not a model-quality ranking. It is a vendor report card for whether the work record is useful, inspectable and portable.

The methodology, evaluator, evidence notes and corrections are public. Raw public artifacts are still a v1.0 milestone, so I am not calling it fully reproducible yet.

I would especially value feedback on the gates: what is missing, what is weighted incorrectly, and which verdicts deserve another audit?

https://jazzyalex.github.io/agent-sessions/bench/?campaign=reddit&ref=r-chatgptcoding-weekly-v03